We present an unsupervised, shape-based method for joint clustering of multiple image segmentations. Given two or more closely-related images, such as nearby frames in a video seq...
We present an unsupervised, shape-based method for joint clustering of multiple image segmentations. Given two or more closely-related images, such as nearby frames in a video sequ...
Daniel Glasner, Shiv N. Vitaladevuni and Ronen Bas...
In this work, we propose a novel saliency-based objective quality assessment metric, for assessing the perceptual quality of decoded video sequences affected by packet loses. The ...
We present a study on the use of soft computing techniques for object tracking/segmentation in surveillance video clips. A number of artificial creatures, conceptually, "inhab...
Embedding generic shape information into probabilistic spatiotemporal video object segmentation is of pivotal importance to achieving better segmentation, since it provides valuab...